AI for coding: from autocomplete to agents
Coding assistance now spans autocomplete, chat, review and autonomous agents. Knowing which to use when avoids wasted effort and avoidable risk.
By the Halden editorial team
The spectrum
Four modes of help.
Autocomplete speeds up typing, chat explains and drafts, review tools check changes, and agents carry out multi-file tasks. Teams often start with the first two and add agents as trust grows.
Best fits
Where AI helps most.
Tests, boilerplate, refactoring, documentation, bug triage and learning an unfamiliar codebase are strong early uses.
- Writing and extending tests.
- Explaining legacy code.
- Migrating or refactoring with clear rules.
Where to be careful
Security, design and ownership.
Security-sensitive code, architecture decisions and anything touching secrets need extra human attention. Generated code can include bugs and licence issues.
Measure
Outcomes over output.
Track cycle time, defect rates and review effort, and gather developer feedback. More code is not the goal; better software delivered sooner is.
A next step
Turn this into a decision for your organization.
Explore how AI Implementation works with leaders and teams, or start with a short reflection on where you are today.